This is the largest retrospective study of cochlear implant outcomes to date, evaluating 2,489 cochlear implant recipients from three clinics. We conduct a thorough examination of machine learning approaches to predict word recognition scores (WRS) measured approximately 12 months after implantation in adults with post-lingual hearing loss. However, existing studies are limited in terms of model validation and evaluating factors like sample size on predictive performance. Several publications indicate that machine learning may improve predictive accuracy of cochlear implant outcomes compared to classical statistical methods. While cochlear implants have helped hundreds of thousands of individuals, it remains difficult to predict the extent to which an individual’s hearing will benefit from implantation. Software-guided methods saved about 10 min of clinician’s time versus standard fittings. Subject-reported speech perception was slightly inferior with the five-electrode method. Speech recognition was not inferior using either version of the electrophysiology-based software-guided fitting method compared with the standard method. Analysis of stimulation levels and ECAP thresholds suggested that the 5-electrode method could be refined. Clinicians judged usability for all methods as acceptable, as did subjects for comfort. However, the 5-electrode method gave scores on the SSQ speech subscale 0.5 points lower than the standard method. Speech recognition in noise and quiet was not significantly different between software- guided and standard methods, but there was a visit/learning-effect. Prospective, double-blind, single-subject repeated-measures with permuted ABCA sequences.Ĥ8 post linguistically deafened adults with ≤15 years of severe-to-profound deafness who were newly unilaterally implanted with a Nucleus device. Objective and subjective performance results were compared between software-guided and clinical fittings. The two versions used electrically evoked compound action potential (ECAP) thresholds for either five or all twenty-two electrodes to determine sound processor stimulation level profiles. This study compared two different versions of an electrophysiology-based software-guided cochlear implant fitting method with a procedure employing standard clinical software.
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